In this paper, we designed a new hyperchaotic two-dimensional map with wide distribution and two large positive Lyapunov exponents. Then, we used it to construct a new randomized bit-level chaotic image encryption algorithm with the proposed hyperchaotic map as the source of randomization for permutation and diffusion. The input image is randomized by appending an extra random row and an additional

Credit scoring is a process of calculating the risk associated with an applicant on the basis of applicant’s credentials such as social status, financial status, etc. and it plays a vital role to improve cash flow for financial industry. However, the credit scoring dataset may have a large number of irrelevant or redundant features which leads to poorer classification performances and higher complexity

Smart TVs offer a variety of features that increase interactivity and available services when compared to other TVs. Furthermore, remote controls have become more complex, with more and smaller buttons, making interaction difficult for people with visual impairments. To address some of these concerns, the solution described herein offers, through a mobile application, a set of alternative interaction

This paper introduces a novel four stage filter algorithm to ameliorate images corrupted by very high density salt-and-pepper noise. The proposed algorithm exhibits two parallel trimmed median filters (TMF) at the initial stage followed by a masking logic that selects denoised pixel based on the priority. To reduce the blurring effect, higher priority is given to TMF with small window size. In the

Due to the poor design of encoding methods or evolutionary operators in previous genetic-algorithm-based integrated scheduling algorithms, this paper proposes an integrated scheduling algorithm based on a hybrid genetic algorithm and tabu search. Firstly, an encoding method based on a dynamic schedulable operation set is proposed. This method cannot only reflect the priority constraints among operations

Twitter is a social media platform which has been proven to be a great tool for insights of emotions about products, policies etc. through a 280-character message called tweet, containing direct and unfiltered emotions by a large amount of user population. Twitter has attracted the attention of many researchers owing to the fact that every tweet is by default, public in nature which is not the case

In spite of the prominence and robustness of iris recognition systems, iris images acquisition using heterogeneous cameras/sensors, is the prime concern in deploying them for wide-scale applications. The textural qualities of iris samples (images) captured through distinct sensors substantially differ due to the differences in illumination and the underlying hardware that yields intra-class variation

User database of the internet is expanding at a swift rate with the dramatic growth of social media. These include information as well as personal opinions about products, ideas, news, politics, etc. These online opinions and reviews act as a word-to-mouth medium for enhancing or diminishing the popularity of a product, item or concept. Thus, automated analysis of the tone of online opinions helps

This study mainly focuses on how social media influences the Saudi restaurant business. Undoubtedly, the modern generation is primarily influenced by social media. Several human activities are associated with and influenced by social media. Internet, specifically social media greatly influences the behavioral patterns of millions of registered Facebook, Instagram, and Twitter users. However, there

Tables 1, 3, 4, 5, 6, 7, 8 and the body texts in the original publication contain incorrect symbols. The original article article has been corrected.

The designing of 2-D digital differentiator is multimodal and high dimensional problem which requires large number of differentiator coefficients to be optimized, hence conventional design techniques will not lead to optimal 2-D differentiator design. Metaheuristic approaches is a good approach to handle multimodal and high dimensional problem under consideration. In this paper, a novel method for

In recent data, Optical character recognition (OCR) systems have laid hands in the field of most popular language recognitions. Unlike other languages, the Tamil language is more complex to recognize, and hence considerable efforts have been laid in literature. However, the models are not yet well-organized for precise recognition of Tamil characters. Thus, the current research work develops a novel

During the era of Industry 4.0, the industrial robot monitoring process is getting success and popularity day by day. It also plays a vital role in the enhancement of robot vision algorithms. This paper proposed a model Deep Three Dimensional Spearman Correlation Analysis (D3D-SCA) to address nonlinear dimensionality reduction in robot vision for three-dimensional data. Dealing with three-dimensional

In this paper, a robust video zero-watermarking scheme for copyright protection using a combination of convolutional neural network (CNN) and self-organizing map (SOM) in polar complex exponential transform (PCET) space is presented. The scheme is developed not only to remedy the existing problems of lacking in some performance assessments but also to enhance the robustness. It starts with extracting

Most existing methods of domain adaptation are proposed for single-source settings, where the source data come from a single domain. However, in practice, the available data generally come from multiple domains with different distributions. In this paper, we propose asymmetric alignment joint consistent regularization (AACR) for multi-source domain adaptation. As for asymmetric alignment, we propose

Segmentation and classification of ultrasonic breast images is extremely critical for medical diagnosis. Over the last years, various techniques have already been presented for this objective. In this paper, a proposed framework is presented to segment a given ultrasonic image with breast tumor and classify the tumor as being benign or malignant. The proposed framework depends on an active contour

3D scanning of the foot is of great significance for footwear customization, intelligent shoe size recommendation and foot disease diagnosis. In this paper, we propose a 3D foot scanning system that consists of four Intel RealSense cameras and one host PC and scans both feet simultaneously. A novel calibration method that is based on a Tower-type block was proposed for calculating the extrinsic parameters

The pedestrian re-identification problem (i.e., re-id) is essential and pre-requisite in multi-camera video surveillance studies, provided the fact that pedestrian targets need to be accurately re-identified across a network of multiple cameras with non-overlapping fields of views before other post-hoc high-level utilizations (i.e., tracking, behaviors analyses, activities monitoring, etc.) can be

To train a convolutional neural network (CNN) from scratch is not suitable for medical image tasks with insufficient data. Benefiting from the transfer learning, the pre-trained CNN model can provide a reliable initial solution for model optimization of medical image classification. A key concern in breast cancer histology classification is that the model should cover the multi-scale features including

The creative cultural product design, relating to both typical regional cultures and traditional cultural elements, is a hot issue in recent years. However, there is still a lack of systematic and efficient designing methods to guide designing practices. In order to fill this research gap, this paper proposes a new design method based on F-AHP (Fuzzy-Analytic Hierarchy Process) and entropy computation

With the rapid development of information technology, social media has been widely used, and Internet information has been exploded, and consumers may experience information overload. Recommender systems using the social recommendation method that integrates social relationship information can provide users with target information that meets their needs. However, most of the existing methods only rely

Improved pixel value ordering utilizes two embedding procedures. These are the maximum and minimum embedding procedures. The maximum embedding procedure modifies a pixel by either 0 or 1, while the minimum embedding procedure modifies a pixel by either 0 or − 1. Our counter-embedding strategy modifies a corner pixel using both embedding procedures. This strategy exploits the opposing distortions of

Stroke is enlisted as one of the leading causes of death and serious disability affecting millions of human lives across the world with high possibilities of becoming an epidemic in the next few decades. Timely detection and prompt decision making pertinent to this disease, plays a major role which can reduce chances of brain death, paralysis and other resultant outcomes. Machine learning algorithms

In this paper, a parallel region merging strategy is proposed for partitioning Synthetic Aperture Radar (SAR) images into several disjoint regions, based on the region adjacency graph (RAG) of an initial partition and the nearest neighbor graph (NNG) produced from the RAG. Developed from the multi-direction ratio edge detector, a multi-scale-multi-direction (MSMD) one is used to extract edge strength

The manual modeling of ancient Chinese architecture is long and tedious work for artists due to the strict and complex construction rules. Existing procedural modeling methods can reduce the modeling workload; however, only limited types of ancient buildings can be made, and users can only edit the building frame and not the components. Therefore, we have improved the existing methods to solve these

Steganography and steganalysis is a relatively new-fangled scientific discipline in security systems and digital forensics, respectively, but one that has matured greatly over the past two decades. In any specialism of human endeavour, it is imperative to periodically pause and review the state of the discipline for what has been achieved till date. This article scrutinizes where the discipline of

In the context of Reversible Data Hiding scheme (RDH), twin image-based methods have been widely used in recent years. Pixels of any cover image block are organized in ascending order and then modify the largest and smallest pixel to embed hidden information exploiting Pixel Value Ordering (PVO) techniques. The DPVO (Directional PVO) has been utilized in three orientations such as a horizontal, vertical

Lightweight cryptography (LWC) is an interesting research area in the field of information security. Some limitations like: increased components usage, time consumption, power consumption and memory requirement mandate the need for lightweight cryptography. One of the proposed algorithms in this field is Speck which was designed by the National Security Agency (NSA) in June 2013. In this paper, we

The Image Source Method (ISM) is one of the most employed techniques to calculate acoustic Room Impulse Responses (RIRs), however, its computational complexity grows fast with the reverberation time of the room and its computation time can be prohibitive for some applications where a huge number of RIRs are needed. In this paper, we present a new implementation that dramatically improves the computation

This paper presents convolutional neural network (CNN)-based single object detection and tracking algorithms. CNN-based object detection methods are directly applicable to static images, but not to videos. On the other hand, model-free visual object tracking methods cannot detect an object until a ground truth bounding box of the target is provided. Moreover, many annotated video datasets of the target

Multi-panel images are increasingly used in research and medical domains for describing complicated situations like results’ comparison in paper; or case depiction of a patient by combining all his medical images into a consolidated image. However, the content based image retrieval (CBIR) systems face the issue of performance decline in terms of poor retrieval accuracy because the individual sub-images

High Dynamic Range (HDR) television promises to display higher brightness and deeper black levels and thus more vivid and realistic images. However, home video distribution and video broadcasting were historically designed for what we now call standard dynamic range screens (SDR). In order to display SDR content on an HDR screen, it is explicitly or implicitly converted, in a process called inverse

The use of sensors for tasks such as (1) interface manipulation, (2) digital games and (3) simulations is quickly becoming commonplace. Novel digital interfaces are being established and, as a result, users are getting better and better at both learning and using them. Medicine, engineering, and entertainment are but a few of the fields making use of sensors for the purpose of scientific progress or

Handwritten word recognition is one of the hot topics in automatic handwritten text recognition that received a lot of attention in recent years. Unlike character recognition, word recognition deals with considerable variations in word shape and written style. This paper proposes a novel deep model for language-independent handwritten word recognition. The proposed deep structure has two parallel stages

Image up-scaling employs various polynomial interpolation schemes for their reduced computational complexity and suitability for various real-time applications. However, they give blurring artifacts in up-scaled images due to the loss of high frequency (HF) information. Likewise, most of the other edge directed and transform domain interpolation schemes available in the literature though produce lesser

Recent advances in the field of object detection and face recognition have made it possible to develop practical video surveillance systems with embedded object detection and face recognition functionalities that are accurate and fast enough for commercial uses. In this paper, we compare some of the latest approaches to object detection and face recognition and provide reasons why they may or may not

Measuring and analyzing the flow of customers in retail stores is essential for a retailer to better comprehend customers’ behavior and support decision-making. Nevertheless, not much attention has been given to the development of novel technologies for automatic people counting. We introduce LRCN-RetailNet: a recurrent neural network architecture capable of learning a non-linear regression model and

Dental caries is one of the oral diseases which are a major health problem for many people across the globe. It can lead to pain, discomfort, disfigurement, and even death in some cases. Dental caries is caused by the infection of the calcified tissue of the teeth. They can be prevented easily by early diagnosis and treated in the early stages. The development of a reliable model for the diagnosis

Nowadays, visual recognition based dynamic hand gesture tracking has gained very considerable attention. Hand gestures can play an important role as a non-touchable communication tool between machines and humans based on using the affordable built-in webcam. The need for replacing touch-based computing devices interaction has been increasing in many fields like healthcare, security, and generally as

Fire is one of the disasters with the highest probability among natural disasters and social disasters. It poses a serious threat to human life and life safety. In order to reduce fire losses, a reliable fire warning method is particularly important. But due to huge variations of smoke in color, shapes, and texture and complex application environments, the existing methods still do not meet the application

Aiming at the research of real-time data transmission and multi-scale image decomposition of embedded optical sensor array, the principle, method and fusion strategy of multi-sensor image fusion are studied comprehensively, thoroughly and systematically by combining the imaging characteristics of source image with multi-scale geometric analysis tools using machine learning algorithm. A new quality

Stereo matching, which is conventionally used for three-dimensional (3D) information acquisition through cameras, is the most actively studied subject in computer vision. To obtain sophisticated 3D information, refining the disparity map in stereo vision is important. The weighted median filter (WMF) is extensively used to eliminate outliers in post-processing. To this end, various studies have implemented

Affective computing, as a novel paradigm, adds a new feature into the human-computer interactions era that brings emotions into the process of design and evaluation. Such condition influences digital games’ not only structural dimension but also content and evaluation areas. This study aims to evaluate the effect of using emotions in the form of facial expressions as a User Interface (UI) and the input

Convolutional neural networks (CNNs) have recently made impressive results for image super-resolution (SR). Our goal is to introduce a new image SR framework rely on a CNN. In this paper, the input image is decomposed into luminance channel and chromatic channels. A designed network based on a residual dense network is introduced to extract the hierarchical features from luminance part. The bicubic

A huge number of items are associated with the Internet of Things (IoT) which is fixed with software, electronics and sensors. It has a wide variety of applications, namely smart homes, smart grids and smart cities. The sensor devices combine with Internet of Things (IoT) operates as robot system to execute data collection task. The IoT control objects, sense devices and gathers data. In crowd sourcing

Recently, there are lots of tracking methods proposed to improve the performance of visual tracking in videos with challenging situations, such as background clutter, severe occlusion, rotation, and so on. In real unmanned aerial vehicle (UAV) based tracking systems, there are various noises occurring during video capturing, transmission, and processing. However, most existing studies pay attention

This paper presents a multi-mode generalized modified transition chaotic map and a switched chaotic encryption scheme based on it. Eight different modes of operation can be selected based on the map graph (concave or convex), the range modification procedure (shrinking or widening) and the sign of one of its independent parameters. The generalization and modification preserve the controllability and

Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate methodology for the processing of bank cheques with minimal human intervention. When it comes to the clearance of the bank cheques and monetary transactions, this should not only be reliable and robust but also save time which is one of the major

The Covid-19 virus outbreak that emerged in China at the end of 2019 caused a huge and devastating effect worldwide. In patients with severe symptoms of the disease, pneumonia develops due to Covid-19 virus. This causes intense involvement and damage in lungs. Although the emergence of the disease occurred a short time ago, many literature studies have been carried out in which these effects of the

This work introduces a novel method for the creation of an in-home virtual dressing room for garment fitting using an integrated system consisting of personalized 3D body model reconstruction and garment fitting simulation. Our method gives saliency to and establishes a relational interconnection between the massive scatter points on the 3D generic model. Starting with a small set of anthropometric

The article title in the original publication of this article contains a mistake.

Social Book Search is an Information Retrieval (IR) approach that studies the impact of the Social Web on book retrieval. To understand this impact, it is necessary to develop a stronger classical baseline run by considering the contribution of query formulation, document representation, and retrieval model. Such a stronger baseline run can be re-ranked using metadata features from the Social Web to

Diabetic retinopathy is the main cause of the blindness worldwide. However, the diabetic retinopathy is hard to be detected in the initial stages, and the procedure of diagnostic can be time-consuming even for experienced-experts. The segment based learning approach has shown the benefits over learning technique for detection of diabetic retinopathy: only the annotation of image level is required get

Surface defect classification (SDC) is the visual inspection of the surface of an object to identify appearance defects. Efficient and accurate SDC is i mportant for improving the quality of industrial products. A manually designed convolutional neural network (CNN) is traditionally used for SDC. In this study, a simpler SDC scheme with a higher classification accuracy, named NAS-SDC, is developed

In this paper, we present a fast multi-stage image segmentation method that incorporates texture analysis into a level set-based active contour framework. This approach allows integrating multiple feature extraction methods and is not tied to any specific texture descriptors. Prior knowledge of the image patterns is also not required. The method starts with an initial feature extraction and selection

Mapping the environment for robot navigation is an important and challenging task in SLAM (Simultaneous Localization And Mapping). Lidar sensor can produce near accurate 3D map of the environment in real time in form of point clouds. Though the point cloud data is adequate for building the map of the environment, processing millions of points in a point cloud is found to be computationally expensive

The common dehazing algorithms always assume that the transmission values of all the pixels in an image block are the same (local consistency assumption). However, it is easy to appear “halo” for image regions where the depth changes obviously. In this paper, we calculate the transmission of each pixel separately without the local consistency assumption. First, we initialize a random transmission value

Security threats are crucial challenges that deter Mixed reality (MR) communication in medical telepresence. This research aims to improve the security by reducing the chances of types of various attacks occurring during the real-time data transmission in surgical telepresence as well as reduce the time of the cryptographic algorithm and keep the quality of the media used. The proposed model consists

Steganalysis is the science for detecting steganographic traces in innocent-looking digital media like images, videos, etc. In recent literature, it has been observed that state-of-the-art image steganographic techniques such as S-UNIWARD, HUGO, WOW, etc. still remain undetected even with considerable embedding payload. Recently, the deep learning framework has been hugely successful in different computer

Motivation: Medical image enhancement is a crucial part to improve the quality of the images. The excellent visual effects and image quality can help doctors make quick diagnoses. Among medical images, Magnetic Resonance Imaging (MRI) images play a vital role in clinical diagnosis. Its imaging principle highlights the human tissue part ignoring the boundary information sometimes. Moreover, some imaging